"""Supermemory memory plugin using the MemoryProvider interface.

Provides semantic long-term memory with profile recall, semantic search,
explicit memory tools, cleaned turn capture, and session-end conversation ingest.
"""

from __future__ import annotations

import json
import logging
import os
import re
import threading
import urllib.error
import urllib.request
from datetime import datetime, timezone
from pathlib import Path
from typing import Any, Dict, List, Optional

from agent.memory_provider import MemoryProvider
from tools.registry import tool_error

logger = logging.getLogger(__name__)

_DEFAULT_CONTAINER_TAG = "hermes"
_DEFAULT_MAX_RECALL_RESULTS = 10
_DEFAULT_PROFILE_FREQUENCY = 50
_DEFAULT_CAPTURE_MODE = "all"
_DEFAULT_SEARCH_MODE = "hybrid"
_VALID_SEARCH_MODES = ("hybrid", "memories", "documents")
_DEFAULT_API_TIMEOUT = 5.0
_MIN_CAPTURE_LENGTH = 10
_MAX_ENTITY_CONTEXT_LENGTH = 1500
_DEFAULT_BASE_URL = "https://api.supermemory.ai"
_API_KEY_URL = "http://app.supermemory.ai/integrations?connect=hermes"
_TRIVIAL_RE = re.compile(
    r"^(ok|okay|thanks|thank you|got it|sure|yes|no|yep|nope|k|ty|thx|np)\.?$",
    re.IGNORECASE,
)
_CONTEXT_STRIP_RE = re.compile(
    r"<supermemory-context>[\s\S]*?</supermemory-context>\s*", re.DOTALL
)
_CONTAINERS_STRIP_RE = re.compile(
    r"<supermemory-containers>[\s\S]*?</supermemory-containers>\s*", re.DOTALL
)
_DEFAULT_ENTITY_CONTEXT = (
    "User-assistant conversation. Format: [role: user]...[user:end] and "
    "[role: assistant]...[assistant:end].\n\n"
    "Only extract things useful in future conversations. Most messages are not worth remembering.\n\n"
    "Remember lasting personal facts, preferences, routines, tools, ongoing projects, working context, "
    "and explicit requests to remember something.\n\n"
    "Do not remember temporary intents, one-time tasks, assistant actions, implementation details, or in-progress status.\n\n"
    "When in doubt, store less."
)


def _default_config() -> dict:
    return {
        "container_tag": _DEFAULT_CONTAINER_TAG,
        "auto_recall": True,
        "auto_capture": True,
        "max_recall_results": _DEFAULT_MAX_RECALL_RESULTS,
        "profile_frequency": _DEFAULT_PROFILE_FREQUENCY,
        "capture_mode": _DEFAULT_CAPTURE_MODE,
        "search_mode": _DEFAULT_SEARCH_MODE,
        "entity_context": _DEFAULT_ENTITY_CONTEXT,
        "api_timeout": _DEFAULT_API_TIMEOUT,
        "base_url": "",
        "enable_custom_container_tags": False,
        "custom_containers": [],
        "custom_container_instructions": "",
    }


def _sanitize_tag(raw: str) -> str:
    tag = re.sub(r"[^a-zA-Z0-9_]", "_", raw or "")
    tag = re.sub(r"_+", "_", tag)
    return tag.strip("_") or _DEFAULT_CONTAINER_TAG


def _resolve_base_url(config_value: Any = "") -> str:
    """Resolve the API base URL: config > SUPERMEMORY_BASE_URL env var > default.

    Supports self-hosted Supermemory servers (e.g. http://localhost:6767).
    """
    raw = (
        str(config_value or "").strip()
        or os.environ.get("SUPERMEMORY_BASE_URL", "").strip()
    )
    return (raw or _DEFAULT_BASE_URL).rstrip("/") or _DEFAULT_BASE_URL


def _clamp_entity_context(text: str) -> str:
    if not text:
        return _DEFAULT_ENTITY_CONTEXT
    text = text.strip()
    return text[:_MAX_ENTITY_CONTEXT_LENGTH]


def _as_bool(value: Any, default: bool) -> bool:
    if isinstance(value, bool):
        return value
    if isinstance(value, str):
        lowered = value.strip().lower()
        if lowered in {"true", "1", "yes", "y", "on"}:
            return True
        if lowered in {"false", "0", "no", "n", "off"}:
            return False
    return default


def _load_supermemory_config(hermes_home: str) -> dict:
    config = _default_config()
    config_path = Path(hermes_home) / "supermemory.json"
    if config_path.exists():
        try:
            raw = json.loads(config_path.read_text(encoding="utf-8"))
            if isinstance(raw, dict):
                config.update({k: v for k, v in raw.items() if v is not None})
        except Exception:
            logger.debug("Failed to parse %s", config_path, exc_info=True)

    # Keep raw container_tag — template variables like {identity} are resolved
    # in initialize(), and _sanitize_tag runs AFTER resolution.
    raw_tag = str(config.get("container_tag", _DEFAULT_CONTAINER_TAG)).strip()
    config["container_tag"] = raw_tag if raw_tag else _DEFAULT_CONTAINER_TAG
    config["auto_recall"] = _as_bool(config.get("auto_recall"), True)
    config["auto_capture"] = _as_bool(config.get("auto_capture"), True)
    try:
        config["max_recall_results"] = max(1, min(20, int(config.get("max_recall_results", _DEFAULT_MAX_RECALL_RESULTS))))
    except Exception:
        config["max_recall_results"] = _DEFAULT_MAX_RECALL_RESULTS
    try:
        config["profile_frequency"] = max(1, min(500, int(config.get("profile_frequency", _DEFAULT_PROFILE_FREQUENCY))))
    except Exception:
        config["profile_frequency"] = _DEFAULT_PROFILE_FREQUENCY
    config["capture_mode"] = "everything" if config.get("capture_mode") == "everything" else "all"
    raw_search_mode = str(config.get("search_mode", _DEFAULT_SEARCH_MODE)).strip().lower()
    config["search_mode"] = raw_search_mode if raw_search_mode in _VALID_SEARCH_MODES else _DEFAULT_SEARCH_MODE
    config["entity_context"] = _clamp_entity_context(str(config.get("entity_context", _DEFAULT_ENTITY_CONTEXT)))
    try:
        config["api_timeout"] = max(0.5, min(15.0, float(config.get("api_timeout", _DEFAULT_API_TIMEOUT))))
    except Exception:
        config["api_timeout"] = _DEFAULT_API_TIMEOUT
    config["base_url"] = str(config.get("base_url", "") or "").strip()

    # Multi-container support
    config["enable_custom_container_tags"] = _as_bool(config.get("enable_custom_container_tags"), False)
    raw_containers = config.get("custom_containers", [])
    if isinstance(raw_containers, list):
        config["custom_containers"] = [_sanitize_tag(str(t)) for t in raw_containers if t]
    else:
        config["custom_containers"] = []
    config["custom_container_instructions"] = str(config.get("custom_container_instructions", "")).strip()

    return config


def _save_supermemory_config(values: dict, hermes_home: str) -> None:
    config_path = Path(hermes_home) / "supermemory.json"
    existing = {}
    if config_path.exists():
        try:
            raw = json.loads(config_path.read_text(encoding="utf-8"))
            if isinstance(raw, dict):
                existing = raw
        except Exception:
            existing = {}
    existing.update(values)
    from utils import atomic_json_write
    atomic_json_write(config_path, existing, mode=0o600, sort_keys=True)


def _detect_category(text: str) -> str:
    lowered = text.lower()
    if re.search(r"prefer|like|love|hate|want", lowered):
        return "preference"
    if re.search(r"decided|will use|going with", lowered):
        return "decision"
    if re.search(r"\bis\b|\bare\b|\bhas\b|\bhave\b", lowered):
        return "fact"
    return "other"


def _format_relative_time(iso_timestamp: str) -> str:
    try:
        dt = datetime.fromisoformat(iso_timestamp.replace("Z", "+00:00"))
        now = datetime.now(timezone.utc)
        seconds = (now - dt).total_seconds()
        if seconds < 1800:
            return "just now"
        if seconds < 3600:
            return f"{int(seconds / 60)}m ago"
        if seconds < 86400:
            return f"{int(seconds / 3600)}h ago"
        if seconds < 604800:
            return f"{int(seconds / 86400)}d ago"
        if dt.year == now.year:
            return dt.strftime("%d %b")
        return dt.strftime("%d %b %Y")
    except Exception:
        return ""


def _deduplicate_recall(static_facts: list, dynamic_facts: list, search_results: list) -> tuple[list, list, list]:
    seen = set()
    out_static, out_dynamic, out_search = [], [], []
    for fact in static_facts or []:
        if fact and fact not in seen:
            seen.add(fact)
            out_static.append(fact)
    for fact in dynamic_facts or []:
        if fact and fact not in seen:
            seen.add(fact)
            out_dynamic.append(fact)
    for item in search_results or []:
        memory = item.get("memory", "")
        if memory and memory not in seen:
            seen.add(memory)
            out_search.append(item)
    return out_static, out_dynamic, out_search


def _format_prefetch_context(static_facts: list, dynamic_facts: list, search_results: list, max_results: int) -> str:
    statics, dynamics, search = _deduplicate_recall(static_facts, dynamic_facts, search_results)
    statics = statics[:max_results]
    dynamics = dynamics[:max_results]
    search = search[:max_results]
    if not statics and not dynamics and not search:
        return ""

    sections = []
    if statics:
        sections.append("## User Profile (Persistent)\n" + "\n".join(f"- {item}" for item in statics))
    if dynamics:
        sections.append("## Recent Context\n" + "\n".join(f"- {item}" for item in dynamics))
    if search:
        lines = []
        for item in search:
            memory = item.get("memory", "")
            if not memory:
                continue
            similarity = item.get("similarity")
            updated = item.get("updated_at") or item.get("updatedAt") or ""
            prefix_bits = []
            rel = _format_relative_time(updated)
            if rel:
                prefix_bits.append(f"[{rel}]")
            if similarity is not None:
                try:
                    prefix_bits.append(f"[{round(float(similarity) * 100)}%]")
                except Exception:
                    pass
            prefix = " ".join(prefix_bits)
            lines.append(f"- {prefix} {memory}".strip())
        if lines:
            sections.append("## Relevant Memories\n" + "\n".join(lines))
    if not sections:
        return ""

    intro = (
        "The following is background context from long-term memory. Use it silently when relevant. "
        "Do not force memories into the conversation."
    )
    body = "\n\n".join(sections)
    return f"<supermemory-context>\n{intro}\n\n{body}\n</supermemory-context>"


def _clean_text_for_capture(text: str) -> str:
    text = _CONTEXT_STRIP_RE.sub("", text or "")
    text = _CONTAINERS_STRIP_RE.sub("", text)
    return text.strip()


def _is_trivial_message(text: str) -> bool:
    return bool(_TRIVIAL_RE.match((text or "").strip()))


class _SupermemoryClient:
    def __init__(self, api_key: str, timeout: float, container_tag: str,
                 search_mode: str = "hybrid", base_url: str = ""):
        # Lazy-install the supermemory SDK on demand. ensure() honors
        # security.allow_lazy_installs (default true) and, on a sealed Docker
        # venv, redirects the install to the durable target. On failure we
        # fall through so the raw import below produces the canonical
        # ImportError message.
        try:
            from tools.lazy_deps import ensure as _lazy_ensure
            _lazy_ensure("memory.supermemory", prompt=False)
        except ImportError:
            pass
        except Exception:
            pass
        from supermemory import Supermemory

        self._api_key = api_key
        self._container_tag = container_tag
        self._search_mode = search_mode if search_mode in _VALID_SEARCH_MODES else _DEFAULT_SEARCH_MODE
        self._timeout = timeout
        self._base_url = _resolve_base_url(base_url)
        self._client = Supermemory(
            api_key=api_key,
            base_url=self._base_url,
            timeout=timeout,
            max_retries=0,
            default_headers={"x-sm-source": "hermes"},
        )

    def _merge_metadata(self, metadata: Optional[dict]) -> dict:
        # sm_source routes Hermes writes into the "Hermes" Space in the Supermemory
        # app so the user can filter / bulk-manage them per source agent. This is a
        # functional routing key for the user, not vendor telemetry.
        merged = {"sm_source": "hermes", **(metadata or {})}
        legacy_source = merged.pop("source", None)
        if legacy_source and "type" not in merged:
            merged["type"] = str(legacy_source)
        return merged

    def add_memory(self, content: str, metadata: Optional[dict] = None, *,
                   entity_context: str = "", container_tag: Optional[str] = None,
                   custom_id: Optional[str] = None) -> dict:
        tag = container_tag or self._container_tag
        kwargs: dict[str, Any] = {
            "content": content.strip(),
            "container_tags": [tag],
        }
        if metadata:
            kwargs["metadata"] = self._merge_metadata(metadata)
        if entity_context:
            kwargs["entity_context"] = _clamp_entity_context(entity_context)
        if custom_id:
            kwargs["custom_id"] = custom_id
        result = self._client.documents.add(**kwargs)
        return {"id": getattr(result, "id", "")}

    def search_memories(self, query: str, *, limit: int = 5,
                        container_tag: Optional[str] = None,
                        search_mode: Optional[str] = None) -> list[dict]:
        tag = container_tag or self._container_tag
        mode = search_mode or self._search_mode
        kwargs: dict[str, Any] = {"q": query, "container_tag": tag, "limit": limit}
        if mode in _VALID_SEARCH_MODES:
            kwargs["search_mode"] = mode
        response = self._client.search.memories(**kwargs)
        results = []
        for item in (getattr(response, "results", None) or []):
            results.append({
                "id": getattr(item, "id", ""),
                "memory": getattr(item, "memory", "") or "",
                "similarity": getattr(item, "similarity", None),
                "updated_at": getattr(item, "updated_at", None) or getattr(item, "updatedAt", None),
                "metadata": getattr(item, "metadata", None),
            })
        return results

    def get_profile(self, query: Optional[str] = None, *,
                    container_tag: Optional[str] = None) -> dict:
        tag = container_tag or self._container_tag
        kwargs: dict[str, Any] = {"container_tag": tag}
        if query:
            kwargs["q"] = query
        response = self._client.profile(**kwargs)
        profile_data = getattr(response, "profile", None)
        search_data = getattr(response, "search_results", None) or getattr(response, "searchResults", None)
        static = getattr(profile_data, "static", []) or [] if profile_data else []
        dynamic = getattr(profile_data, "dynamic", []) or [] if profile_data else []
        raw_results = getattr(search_data, "results", None) or search_data or []
        search_results = []
        if isinstance(raw_results, list):
            for item in raw_results:
                if isinstance(item, dict):
                    search_results.append(item)
                else:
                    search_results.append({
                        "memory": getattr(item, "memory", ""),
                        "updated_at": getattr(item, "updated_at", None) or getattr(item, "updatedAt", None),
                        "similarity": getattr(item, "similarity", None),
                    })
        return {"static": static, "dynamic": dynamic, "search_results": search_results}

    def forget_memory(self, memory_id: str, *, container_tag: Optional[str] = None) -> None:
        tag = container_tag or self._container_tag
        self._client.memories.forget(container_tag=tag, id=memory_id)

    def forget_by_query(self, query: str, *, container_tag: Optional[str] = None) -> dict:
        results = self.search_memories(query, limit=5, container_tag=container_tag)
        if not results:
            return {"success": False, "message": "No matching memory found to forget."}
        target = results[0]
        memory_id = target.get("id", "")
        if not memory_id:
            return {"success": False, "message": "Best matching memory has no id."}
        self.forget_memory(memory_id, container_tag=container_tag)
        preview = (target.get("memory") or "")[:100]
        return {"success": True, "message": f'Forgot: "{preview}"', "id": memory_id}

    def ingest_conversation(self, session_id: str, messages: list[dict], metadata: dict | None = None) -> None:
        payload: dict = {
            "conversationId": session_id,
            "messages": messages,
            "containerTags": [self._container_tag],
        }
        if metadata:
            payload["metadata"] = self._merge_metadata(metadata)

        req = urllib.request.Request(
            f"{self._base_url}/v4/conversations",
            data=json.dumps(payload).encode("utf-8"),
            headers={
                "Authorization": f"Bearer {self._api_key}",
                "Content-Type": "application/json",
                "x-sm-source": "hermes",
            },
            method="POST",
        )
        with urllib.request.urlopen(req, timeout=self._timeout + 3):
            return


def _resolve_container_tag_for_setup(hermes_home: str, *, identity: str = "default") -> str:
    config = _load_supermemory_config(hermes_home)
    env_tag = os.environ.get("SUPERMEMORY_CONTAINER_TAG", "").strip()
    raw_tag = env_tag or config["container_tag"]
    return _sanitize_tag(raw_tag.replace("{identity}", identity))


def _probe_supermemory_connection(api_key: str, hermes_home: str, *, identity: str = "default") -> dict:
    config = _load_supermemory_config(hermes_home)
    base_url = _resolve_base_url(config["base_url"])
    status = {
        "ok": False,
        "error": "",
        "container_tag": _resolve_container_tag_for_setup(hermes_home, identity=identity),
        "profile_facts": 0,
        "auto_recall": bool(config["auto_recall"]),
        "auto_capture": bool(config["auto_capture"]),
    }
    if not (api_key or "").strip():
        status["error"] = "SUPERMEMORY_API_KEY not set"
        return status
    try:
        __import__("supermemory")
    except ImportError:
        status["error"] = "supermemory package not installed"
        return status
    try:
        client = _SupermemoryClient(
            api_key=api_key.strip(),
            timeout=config["api_timeout"],
            container_tag=status["container_tag"],
            search_mode=config["search_mode"],
            base_url=base_url,
        )
        profile = client.get_profile()
        facts = [
            fact for fact in (profile.get("static") or []) + (profile.get("dynamic") or [])
            if fact and str(fact).strip()
        ]
        status["profile_facts"] = len(facts)
        status["ok"] = True
    except Exception as exc:
        status["error"] = str(exc).strip()[:160] or "connection failed"
    return status


def _format_connection_summary(status: dict) -> str:
    recall = "on" if status.get("auto_recall") else "off"
    capture = "on" if status.get("auto_capture") else "off"
    container = status.get("container_tag") or _DEFAULT_CONTAINER_TAG
    if status.get("ok"):
        facts = int(status.get("profile_facts") or 0)
        fact_label = "fact" if facts == 1 else "facts"
        return (
            f"✓ Connected · container: {container} · {facts} profile {fact_label} · "
            f"auto_recall {recall} · auto_capture {capture}"
        )
    err = status.get("error") or "connection failed"
    return f"✗ {err} · container: {container} · auto_recall {recall} · auto_capture {capture}"


STORE_SCHEMA = {
    "name": "supermemory_store",
    "description": "Store an explicit memory for future recall.",
    "parameters": {
        "type": "object",
        "properties": {
            "content": {"type": "string", "description": "The memory content to store."},
            "metadata": {"type": "object", "description": "Optional metadata attached to the memory."},
        },
        "required": ["content"],
    },
}

SEARCH_SCHEMA = {
    "name": "supermemory_search",
    "description": "Search long-term memory by semantic similarity.",
    "parameters": {
        "type": "object",
        "properties": {
            "query": {"type": "string", "description": "What to search for."},
            "limit": {"type": "integer", "description": "Maximum results to return, 1 to 20."},
        },
        "required": ["query"],
    },
}

FORGET_SCHEMA = {
    "name": "supermemory_forget",
    "description": "Forget a memory by exact id or by best-match query.",
    "parameters": {
        "type": "object",
        "properties": {
            "id": {"type": "string", "description": "Exact memory id to delete."},
            "query": {"type": "string", "description": "Query used to find the memory to forget."},
        },
    },
}

PROFILE_SCHEMA = {
    "name": "supermemory_profile",
    "description": "Retrieve persistent profile facts and recent memory context.",
    "parameters": {
        "type": "object",
        "properties": {
            "query": {"type": "string", "description": "Optional query to focus the profile response."},
        },
    },
}


class SupermemoryMemoryProvider(MemoryProvider):
    def __init__(self):
        self._config = _default_config()
        self._api_key = ""
        self._client: Optional[_SupermemoryClient] = None
        self._container_tag = _DEFAULT_CONTAINER_TAG
        self._session_id = ""
        self._turn_count = 0
        self._prefetch_result = ""
        self._prefetch_lock = threading.Lock()
        self._prefetch_thread: Optional[threading.Thread] = None
        self._sync_thread: Optional[threading.Thread] = None
        self._write_thread: Optional[threading.Thread] = None
        self._auto_recall = True
        self._auto_capture = True
        self._max_recall_results = _DEFAULT_MAX_RECALL_RESULTS
        self._profile_frequency = _DEFAULT_PROFILE_FREQUENCY
        self._capture_mode = _DEFAULT_CAPTURE_MODE
        self._search_mode = _DEFAULT_SEARCH_MODE
        self._entity_context = _DEFAULT_ENTITY_CONTEXT
        self._api_timeout = _DEFAULT_API_TIMEOUT
        self._base_url = _DEFAULT_BASE_URL
        self._hermes_home = ""
        self._write_enabled = True
        self._active = False
        # Multi-container support
        self._enable_custom_containers = False
        self._custom_containers: List[str] = []
        self._custom_container_instructions = ""
        self._allowed_containers: List[str] = []
        self._session_turns: List[Dict[str, str]] = []

    @property
    def name(self) -> str:
        return "supermemory"

    def is_available(self) -> bool:
        # Key presence only — no SDK import check. The supermemory SDK is
        # lazy-installed when the client is first constructed in initialize()
        # (see _SupermemoryClient.__init__). Gating availability on the SDK
        # being importable here would be a chicken-and-egg trap: on a sealed
        # Docker venv the package isn't present until ensure() runs, but
        # ensure() only runs once the provider is loaded — which this gates.
        # Mirrors honcho/mem0, which check config only. No network calls.
        return bool(os.environ.get("SUPERMEMORY_API_KEY", ""))

    def get_config_schema(self):
        # Only prompt for the API key during `hermes memory setup`.
        # All other options are documented for $HERMES_HOME/supermemory.json
        # or the SUPERMEMORY_CONTAINER_TAG env var.
        return [
            {"key": "api_key", "description": "Supermemory API key", "secret": True, "required": True, "env_var": "SUPERMEMORY_API_KEY", "url": _API_KEY_URL},
        ]

    def save_config(self, values, hermes_home):
        sanitized = dict(values or {})
        if "container_tag" in sanitized:
            sanitized["container_tag"] = _sanitize_tag(str(sanitized["container_tag"]))
        if "entity_context" in sanitized:
            sanitized["entity_context"] = _clamp_entity_context(str(sanitized["entity_context"]))
        _save_supermemory_config(sanitized, hermes_home)

    def get_status_config(self, provider_config: dict) -> dict:
        from hermes_constants import get_hermes_home

        del provider_config
        hermes_home = str(get_hermes_home())
        api_key = os.environ.get("SUPERMEMORY_API_KEY", "")
        status = _probe_supermemory_connection(api_key, hermes_home)
        return {"summary": _format_connection_summary(status)}

    def post_setup(self, hermes_home: str, config: dict) -> None:
        from pathlib import Path

        from hermes_cli.config import save_config
        from hermes_cli.memory_setup import _prompt, _write_env_vars

        print("\n  Configuring supermemory:\n")
        print(f"  Get your API key at {_API_KEY_URL}\n")

        env_writes: dict[str, str] = {}
        existing = os.environ.get("SUPERMEMORY_API_KEY", "")
        if existing:
            masked = f"...{existing[-4:]}" if len(existing) > 4 else "set"
            val = _prompt(f"Supermemory API key (current: {masked}, blank to keep)", secret=True)
        else:
            val = _prompt("Supermemory API key", secret=True)
        if val:
            env_writes["SUPERMEMORY_API_KEY"] = val

        if not isinstance(config.get("memory"), dict):
            config["memory"] = {}
        config["memory"]["provider"] = self.name
        save_config(config)

        if env_writes:
            _write_env_vars(Path(hermes_home) / ".env", env_writes)

        api_key = env_writes.get("SUPERMEMORY_API_KEY") or existing
        # Make the freshly-entered key visible to the connection probe below.
        # (Checks the VALUE of SUPERMEMORY_API_KEY, not whether the key string
        # happens to name some unrelated env var.)
        if api_key and os.environ.get("SUPERMEMORY_API_KEY") != api_key:
            os.environ["SUPERMEMORY_API_KEY"] = api_key

        status = _probe_supermemory_connection(api_key, hermes_home)
        print(f"\n  {_format_connection_summary(status)}")
        print("\n  Memory provider: supermemory")
        print("  Activation saved to config.yaml")
        if env_writes:
            print("  API keys saved to .env")
        print("\n  Start a new session to activate.\n")

    def initialize(self, session_id: str, **kwargs) -> None:
        from hermes_constants import get_hermes_home
        self._hermes_home = kwargs.get("hermes_home") or str(get_hermes_home())
        self._session_id = session_id
        self._turn_count = 0
        self._config = _load_supermemory_config(self._hermes_home)
        self._api_key = os.environ.get("SUPERMEMORY_API_KEY", "")

        # Resolve container tag: env var > config > default.
        # Supports {identity} template for profile-scoped containers.
        env_tag = os.environ.get("SUPERMEMORY_CONTAINER_TAG", "").strip()
        raw_tag = env_tag or self._config["container_tag"]
        identity = kwargs.get("agent_identity", "default")
        self._container_tag = _sanitize_tag(raw_tag.replace("{identity}", identity))

        self._auto_recall = self._config["auto_recall"]
        self._auto_capture = self._config["auto_capture"]
        self._max_recall_results = self._config["max_recall_results"]
        self._profile_frequency = self._config["profile_frequency"]
        self._capture_mode = self._config["capture_mode"]
        self._search_mode = self._config["search_mode"]
        self._entity_context = self._config["entity_context"]
        self._api_timeout = self._config["api_timeout"]
        # Base URL: config > SUPERMEMORY_BASE_URL env var > api.supermemory.ai.
        # Supports self-hosted Supermemory servers.
        self._base_url = _resolve_base_url(self._config["base_url"])
        self._enable_custom_containers = self._config["enable_custom_container_tags"]
        self._custom_containers = self._config["custom_containers"]
        self._custom_container_instructions = self._config["custom_container_instructions"]
        self._allowed_containers = [self._container_tag] + list(self._custom_containers)

        self._session_turns = []

        agent_context = kwargs.get("agent_context", "")
        self._write_enabled = agent_context not in {"cron", "flush", "subagent"}
        self._active = bool(self._api_key)
        self._client = None
        if self._active:
            try:
                self._client = _SupermemoryClient(
                    api_key=self._api_key,
                    timeout=self._api_timeout,
                    container_tag=self._container_tag,
                    search_mode=self._search_mode,
                    base_url=self._base_url,
                )
            except Exception:
                logger.warning("Supermemory initialization failed", exc_info=True)
                self._active = False
                self._client = None

    def on_turn_start(self, turn_number: int, message: str, **kwargs) -> None:
        self._turn_count = max(turn_number, 0)

    def system_prompt_block(self) -> str:
        if not self._active:
            return ""
        lines = [
            "# Supermemory",
            f"Active. Container: {self._container_tag}.",
            "Use supermemory-search, supermemory-save, supermemory-forget, and supermemory-profile (aliases: supermemory_search, supermemory_store, supermemory_forget, supermemory_profile).",
        ]
        if self._enable_custom_containers and self._custom_containers:
            tags_str = ", ".join(self._allowed_containers)
            lines.append(f"\nMulti-container mode enabled. Available containers: {tags_str}.")
            lines.append("Pass an optional container_tag to supermemory_search, supermemory_store, supermemory_forget, and supermemory_profile to target a specific container.")
            if self._custom_container_instructions:
                lines.append(f"\n{self._custom_container_instructions}")
        return "\n".join(lines)

    def prefetch(self, query: str, *, session_id: str = "") -> str:
        if not self._active or not self._auto_recall or not self._client or not query.strip():
            return ""
        try:
            profile = self._client.get_profile(query=query[:200])
            include_profile = self._turn_count <= 1 or (self._turn_count % self._profile_frequency == 0)
            context = _format_prefetch_context(
                static_facts=profile["static"] if include_profile else [],
                dynamic_facts=profile["dynamic"] if include_profile else [],
                search_results=profile["search_results"],
                max_results=self._max_recall_results,
            )
            return context
        except Exception:
            logger.debug("Supermemory prefetch failed", exc_info=True)
            return ""

    def sync_turn(self, user_content: str, assistant_content: str, *, session_id: str = "") -> None:
        if not self._active or not self._auto_capture or not self._write_enabled or not self._client:
            return

        clean_user = _clean_text_for_capture(user_content)
        clean_assistant = _clean_text_for_capture(assistant_content)
        if not clean_user and not clean_assistant:
            return

        # Buffer every turn for the single full-session document written at end/switch/shutdown
        self._session_turns.append({"user": clean_user, "assistant": clean_assistant})

    def on_session_end(self, messages: List[Dict[str, Any]]) -> None:
        if not self._active or not self._write_enabled or not self._client or not self._session_id:
            return
        cleaned = []
        for message in messages or []:
            role = message.get("role")
            if role not in {"user", "assistant"}:
                continue
            content = _clean_text_for_capture(str(message.get("content", "")))
            if content:
                cleaned.append({"role": role, "content": content})
        if not cleaned:
            return
        if len(cleaned) == 1 and len(cleaned[0].get("content", "")) < 20:
            return
        try:
            self._client.ingest_conversation(
                self._session_id,
                cleaned,
                metadata={
                    "type": "full_session",
                    "session_id": self._session_id,
                    "message_count": len(cleaned),
                },
            )
        except urllib.error.HTTPError:
            logger.warning("Supermemory session ingest failed", exc_info=True)
        except Exception:
            logger.warning("Supermemory session ingest failed", exc_info=True)

        # Clear buffer so shutdown() doesn't duplicate on normal exit
        self._session_turns = []

    def on_session_switch(
        self,
        new_session_id: str,
        *,
        parent_session_id: str = "",
        reset: bool = False,
        **kwargs,
    ) -> None:
        """Flush any buffered turns from the old session as one document, then reset for the new session."""
        if not self._active or not self._write_enabled or not self._client:
            self._session_id = str(new_session_id or "").strip() or self._session_id
            self._session_turns = []
            return

        old_session_id = self._session_id
        old_turns = list(self._session_turns)

        # Flush previous session via conversations ingest (with metadata)
        if old_turns and old_session_id:
            messages: list[dict] = []
            for turn in old_turns:
                if turn.get("user"):
                    messages.append({"role": "user", "content": turn["user"]})
                if turn.get("assistant"):
                    messages.append({"role": "assistant", "content": turn["assistant"]})

            try:
                self._client.ingest_conversation(
                    old_session_id,
                    messages,
                    metadata={
                        "type": "full_session",
                        "session_id": old_session_id,
                        "message_count": len(old_turns) * 2,
                        "partial": not reset,
                    },
                )
            except Exception:
                logger.debug("Supermemory session-switch ingest failed", exc_info=True)

        # Reset for new session
        self._session_id = str(new_session_id or "").strip() or old_session_id
        self._session_turns = []
        self._turn_count = 0

    def on_memory_write(self, action: str, target: str, content: str) -> None:
        if not self._active or not self._write_enabled or not self._client:
            return
        if action != "add" or not (content or "").strip():
            return

        def _run():
            try:
                self._client.add_memory(
                    content.strip(),
                    metadata={"target": target, "type": "explicit_memory"},
                    entity_context=self._entity_context,
                )
            except Exception:
                logger.debug("Supermemory on_memory_write failed", exc_info=True)

        if self._write_thread and self._write_thread.is_alive():
            self._write_thread.join(timeout=2.0)
        self._write_thread = None
        self._write_thread = threading.Thread(target=_run, daemon=False, name="supermemory-memory-write")
        self._write_thread.start()

    def shutdown(self) -> None:
        # Emergency fallback (crashes only). Buffer is cleared on normal on_session_end().
        if self._active and self._write_enabled and self._client and self._session_turns and self._session_id:
            logger.warning("Supermemory: Saving session via shutdown (session=%s, turns=%d)", self._session_id, len(self._session_turns))

            messages: list[dict] = []
            for turn in self._session_turns:
                if turn.get("user"):
                    messages.append({"role": "user", "content": turn["user"]})
                if turn.get("assistant"):
                    messages.append({"role": "assistant", "content": turn["assistant"]})

            try:
                self._client.ingest_conversation(
                    self._session_id,
                    messages,
                    metadata={
                        "type": "full_session",
                        "session_id": self._session_id,
                        "message_count": len(self._session_turns) * 2,
                        "partial": True,
                    },
                )
            except Exception:
                logger.debug("Supermemory shutdown ingest failed", exc_info=True)

        for attr_name in ("_prefetch_thread", "_sync_thread", "_write_thread"):
            thread = getattr(self, attr_name, None)
            if thread and thread.is_alive():
                thread.join(timeout=5.0)
            setattr(self, attr_name, None)

    def _resolve_tool_container_tag(self, args: dict) -> Optional[str]:
        """Validate and resolve container_tag from tool call args.

        Returns None (use primary) if multi-container is disabled or no tag provided.
        Returns the validated tag if it's in the allowed list.
        Raises ValueError if the tag is not whitelisted.
        """
        if not self._enable_custom_containers:
            return None
        tag = str(args.get("container_tag") or "").strip()
        if not tag:
            return None
        sanitized = _sanitize_tag(tag)
        if sanitized not in self._allowed_containers:
            raise ValueError(
                f"Container tag '{sanitized}' is not allowed. "
                f"Allowed: {', '.join(self._allowed_containers)}"
            )
        return sanitized

    def get_tool_schemas(self) -> List[Dict[str, Any]]:
        def with_kebab_aliases(schemas: List[Dict[str, Any]]) -> List[Dict[str, Any]]:
            aliases = {
                "supermemory_store": "supermemory-save",
                "supermemory_search": "supermemory-search",
                "supermemory_forget": "supermemory-forget",
                "supermemory_profile": "supermemory-profile",
            }
            expanded = list(schemas)
            for schema in schemas:
                kebab = aliases.get(schema.get("name", ""))
                if not kebab:
                    continue
                copy = json.loads(json.dumps(schema))
                copy["name"] = kebab
                expanded.append(copy)
            return expanded

        if not self._enable_custom_containers:
            return with_kebab_aliases([STORE_SCHEMA, SEARCH_SCHEMA, FORGET_SCHEMA, PROFILE_SCHEMA])

        # When multi-container is enabled, add optional container_tag to relevant tools
        container_param = {
            "type": "string",
            "description": f"Optional container tag. Allowed: {', '.join(self._allowed_containers)}. Defaults to primary ({self._container_tag}).",
        }
        schemas = []
        for base in [STORE_SCHEMA, SEARCH_SCHEMA, FORGET_SCHEMA, PROFILE_SCHEMA]:
            schema = json.loads(json.dumps(base))  # deep copy
            schema["parameters"]["properties"]["container_tag"] = container_param
            schemas.append(schema)
        return with_kebab_aliases(schemas)

    def _tool_store(self, args: dict) -> str:
        content = str(args.get("content") or "").strip()
        if not content:
            return tool_error("content is required")
        try:
            tag = self._resolve_tool_container_tag(args)
        except ValueError as exc:
            return tool_error(str(exc))
        metadata = args.get("metadata") or {}
        if not isinstance(metadata, dict):
            metadata = {}
        metadata.setdefault("type", _detect_category(content))
        metadata.pop("source", None)
        try:
            result = self._client.add_memory(content, metadata=metadata, entity_context=self._entity_context, container_tag=tag)
            preview = content[:80] + ("..." if len(content) > 80 else "")
            resp: dict[str, Any] = {"saved": True, "id": result.get("id", ""), "preview": preview}
            if tag:
                resp["container_tag"] = tag
            return json.dumps(resp)
        except Exception as exc:
            return tool_error(f"Failed to store memory: {exc}")

    def _tool_search(self, args: dict) -> str:
        query = str(args.get("query") or "").strip()
        if not query:
            return tool_error("query is required")
        try:
            tag = self._resolve_tool_container_tag(args)
        except ValueError as exc:
            return tool_error(str(exc))
        try:
            limit = max(1, min(20, int(args.get("limit", 5) or 5)))
        except Exception:
            limit = 5
        try:
            results = self._client.search_memories(query, limit=limit, container_tag=tag)
            formatted = []
            for item in results:
                entry: dict[str, Any] = {"id": item.get("id", ""), "content": item.get("memory", "")}
                if item.get("similarity") is not None:
                    try:
                        entry["similarity"] = round(float(item["similarity"]) * 100)
                    except Exception:
                        pass
                formatted.append(entry)
            resp: dict[str, Any] = {"results": formatted, "count": len(formatted)}
            if tag:
                resp["container_tag"] = tag
            return json.dumps(resp)
        except Exception as exc:
            return tool_error(f"Search failed: {exc}")

    def _tool_forget(self, args: dict) -> str:
        memory_id = str(args.get("id") or "").strip()
        query = str(args.get("query") or "").strip()
        if not memory_id and not query:
            return tool_error("Provide either id or query")
        try:
            tag = self._resolve_tool_container_tag(args)
        except ValueError as exc:
            return tool_error(str(exc))
        try:
            if memory_id:
                self._client.forget_memory(memory_id, container_tag=tag)
                return json.dumps({"forgotten": True, "id": memory_id})
            return json.dumps(self._client.forget_by_query(query, container_tag=tag))
        except Exception as exc:
            return tool_error(f"Forget failed: {exc}")

    def _tool_profile(self, args: dict) -> str:
        query = str(args.get("query") or "").strip() or None
        try:
            tag = self._resolve_tool_container_tag(args)
        except ValueError as exc:
            return tool_error(str(exc))
        try:
            profile = self._client.get_profile(query=query, container_tag=tag)
            sections = []
            if profile["static"]:
                sections.append("## User Profile (Persistent)\n" + "\n".join(f"- {item}" for item in profile["static"]))
            if profile["dynamic"]:
                sections.append("## Recent Context\n" + "\n".join(f"- {item}" for item in profile["dynamic"]))
            resp: dict[str, Any] = {
                "profile": "\n\n".join(sections),
                "static_count": len(profile["static"]),
                "dynamic_count": len(profile["dynamic"]),
            }
            if tag:
                resp["container_tag"] = tag
            return json.dumps(resp)
        except Exception as exc:
            return tool_error(f"Profile failed: {exc}")

    def handle_tool_call(self, tool_name: str, args: Dict[str, Any], **kwargs) -> str:
        if not self._active or not self._client:
            return tool_error("Supermemory is not configured")
        aliases = {
            "supermemory-save": "supermemory_store",
            "supermemory-search": "supermemory_search",
            "supermemory-forget": "supermemory_forget",
            "supermemory-profile": "supermemory_profile",
        }
        tool_name = aliases.get(tool_name, tool_name)
        if tool_name == "supermemory_store":
            return self._tool_store(args)
        if tool_name == "supermemory_search":
            return self._tool_search(args)
        if tool_name == "supermemory_forget":
            return self._tool_forget(args)
        if tool_name == "supermemory_profile":
            return self._tool_profile(args)
        return tool_error(f"Unknown tool: {tool_name}")


def register(ctx):
    ctx.register_memory_provider(SupermemoryMemoryProvider())
